A man weighs 95 kg and starts an exercise and eating programme to lose weight. If he sticks to the programme, he will lose 0,4 kg per week. Calculate how much he will weigh after 36 weeks.​

The distance around a hockey rink, ignoring the corner rounding, is 570 feet. To find the distance around the hockey rink, we need to calculate the perimeter of the rectangle.

The perimeter of a rectangle is given by the formula: perimeter = 2 * (length + width).

In this case, the length of the rectangle is 200 feet and the width is 85 feet. Substituting these values into the formula, we have perimeter = 2 * (200 + 85) = 2 * 285 = 570 feet.

Therefore, the distance around a hockey rink, ignoring the corner rounding, is 570 feet, which corresponds to option A) 570 ft.

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The Cauchy stress vector [tex]t^n[/tex] on the plane passing through point P with a normal vector [tex]n = 3e_1 + e_2 - 2e_3 \: is \: t^n = [3; 12; 1] \: MPa.[/tex]

The angle between [tex]t^n[/tex] and the vector normal to the plane is approximately 1.147 radians or 65.72 degrees.

The normal component of [tex]t^n[/tex] on the plane is approximately 5.08 MPa, and the shear component is [-2.08; 6.92; 1] MPa.

To determine the Cauchy stress vector, denoted as [tex]t^n[/tex], on the plane passing through point P with a normal vector

[tex]n = 3e_1 + e_2 - 2e_3[/tex], we can use the formula:

[tex]t^n = [ \sigma] · n[/tex] where σ is the Cauchy stress tensor and · denotes tensor contraction. Let's calculate [tex]t^n[/tex]

[tex][2 5 3; 5 1 4; 3 4 3] · [3; 1; -2] = [23 + 51 + 3*(-2); 53 + 11 + 4*(-2); 33 + 41 + 3*(-2)] = [3; 12; 1][/tex]

Therefore, the Cauchy stress vector [tex]t^n[/tex] on the plane passing through point P with a normal vector [tex]n = 3e_1 + e_2 - 2e_3 \: is \: t^n = [3; 12; 1] \: MPa.[/tex]

To find the length of [tex]t^n[/tex], we can calculate the magnitude of the stress vector:

[tex]|t^n| = \sqrt((3^2) + (12^2) + (1^2)) = \sqrt(9 + 144 + 1) = \sqrt(154) ≈ 12.42 \: MPa.[/tex]

The length of [tex]t^n[/tex] is approximately 12.42 MPa.

To find the angle between [tex]t^n[/tex] and the vector normal to the plane, we can use the dot product formula:

[tex]cos( \theta) = (t^n · n) / (|t^n| * |n|)[/tex]

The vector normal to the plane is [tex]n = 3e_1 + e_2 - 2e_3[/tex]

So its magnitude is [tex]|n| = \sqrt((3^2) + (1^2) + (-2^2)) = \sqrt (9 + 1 + 4) = \sqrt(14) ≈ 3.74.[/tex]

[tex]cos( \theta) = ([3; 12; 1] · [3; 1; -2]) / (12.42 * 3.74) = (33 + 121 + 1*(-2)) / (12.42 * 3.74) = (9 + 12 - 2) / (12.42 * 3.74) = 19 / (12.42 * 3.74) ≈ 0.404

[/tex]

[tex] \theta = acos(0.404) ≈ 1.147 \: radians \: or ≈ 65.72 \: degrees[/tex]

The angle between [tex]t^n[/tex] and the vector normal to the plane is approximately 1.147 radians or 65.72 degrees.

To find the normal and shear components of t on the plane, we can decompose [tex]t^n[/tex] into its normal and shear components using the following formulas:

[tex]t^n_{normal} = (t^n · n) / |n| = ([3; 12; 1] · [3; 1; -2]) / 3.74 ≈ 19 / 3.74 ≈ 5.08 \: MPa \\ t^n_{shear} = t^n - t^n_{normal} = [3; 12; 1] - [5.08; 5.08; 0] = [-2.08; 6.92; 1] \: MPa[/tex]

The normal component of [tex]t^n[/tex] on the plane is approximately 5.08 MPa, and the shear component is [-2.08; 6.92; 1] MPa.

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The correct answer is a. 0. the mean difference score (µ d ) equals 0

In a correlated t-test, if the independent variable has no effect, the sample difference scores are expected to be a random sample from a population where the mean difference score (µd) equals 0.

When the independent variable has no effect, it means that there is no systematic difference between the two conditions or time points being compared. In this case, the average difference between the paired observations is expected to be zero, indicating no change or effect. Thus, the mean difference score (µd) is equal to 0.

Therefore, the correct answer is a. 0.

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The weight of the risk-free asset is 0.09 and the weight of the stock is 0.91.

The beta of the portfolio is 0.846.

a. The expected return on a portfolio that is equally invested in the two assets can be calculated as follows:

Expected return = (weight of stock x expected return of stock) + (weight of risk-free asset x expected return of risk-free asset)

Let's assume that the weight of both assets is 0.5:

Expected return = (0.5 x 10.5%) + (0.5 x 2.4%)

Expected return = 6.45% + 1.2%

Expected return = 7.65%

b. The portfolio weights can be calculated using the following formula:

Portfolio beta = (weight of stock x stock beta) + (weight of risk-free asset x risk-free beta)

Let's assume that the weight of the risk-free asset is w and the weight of the stock is (1-w). Also, we know that the portfolio beta is 0.92. Then we have:

0.92 = (1-w) x 1.14 + w x 0

0.92 = 1.14 - 1.14w

1.14w = 1.14 - 0.92

w = 0.09

c. The expected return-beta relationship can be represented by the following formula:

Expected return = risk-free rate + beta x (expected market return - risk-free rate)

Let's assume that the expected return of the portfolio is 9%. Then we have:

9% = 2.4% + beta x (10.5% - 2.4%)

6.6% = 7.8% beta

beta = 0.846

d. Similarly to part (b), the portfolio weights can be calculated using the following formula:

Portfolio beta = (weight of stock x stock beta) + (weight of risk-free asset x risk-free beta)

Let's assume that the weight of the risk-free asset is w and the weight of the stock is (1-w). Also, we know that the portfolio beta is 2.28. Then we have:

2.28 = (1-w) x 1.14 + w x 0

2.28 = 1.14 - 1.14w

1.14w = 1.14 - 2.28

w = -1

This is not a valid result since the weight of the risk-free asset cannot be negative. Therefore, there is no solution to this part.

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The eigenvector corresponding to the eigenvalue 4.

To find the eigenvectors of matrix A, we need to solve the equation Ax = λx, where λ is the eigenvalue and x is the eigenvector.

For λ = -5:

We need to solve the equation (A + 5I)x = 0, where I is the identity matrix.

(A + 5I) = ⎡⎣⎢21−15−12−11727−27−23⎤⎦⎥

Reducing this matrix to row echelon form, we get:

⎡⎣⎢100−12−37350−27−23⎤⎦⎥

The solution to this system is x1 = 2, x2 = 1, and x3 = 3. Therefore, the eigenvector corresponding to the eigenvalue -5 is:

x = ⎡⎣⎢2 1 3⎤⎦⎥

For λ = 1:

We need to solve the equation (A - I)x = 0.

(A - I) = ⎡⎣⎢51−15−12−67627−27−23⎤⎦⎥

Reducing this matrix to row echelon form, we get:

⎡⎣⎢100−12−37300−3−13⎤⎦⎥

The solution to this system is x1 = 1, x2 = 1, and x3 = 0. Therefore, the eigenvector corresponding to the eigenvalue 1 is:

x = ⎡⎣⎢1 1 0⎤⎦⎥

For λ = 4:

We need to solve the equation (A - 4I)x = 0.

(A - 4I) = ⎡⎣⎢1215−12−67627−27−63⎤⎦⎥

Reducing this matrix to row echelon form, we get:

⎡⎣⎢100−16−15−3830−27−63⎤⎦⎥

The solution to this system is x1 = 3, x2 = 1, and x3 = 1. Therefore, the eigenvector corresponding to the eigenvalue 4 is:

x = ⎡⎣⎢3 1 1⎤⎦⎥

Therefore, the eigenvectors of the matrix A are:

x1 = ⎡⎣⎢2 1 3⎤⎦⎥, x2 = ⎡⎣⎢1 1 0⎤⎦⎥, and x3 = ⎡⎣⎢3 1 1⎤⎦⎥

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The scenario that is an example of voluntary sampling is the People's Choice Award given out by the music festival.

In this scenario, participants voluntarily choose to text their choice to the festival sponsor, making it a form of voluntary sampling.

Voluntary sampling involves participants self-selecting themselves into a study or survey, as opposed to being selected randomly or through a predetermined method.

This method can result in biased or non-representative samples, as participants may have specific characteristics or biases that differ from the general population.

It is generally not considered a reliable method for obtaining unbiased results.

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The particular solution is:

y(t) = (t3/3 − t2 + t/3) e−t + (1/3) e−t (t2 + 2t + 2)

To use convolutions to solve the ordinary differential equation y′′ − 2y′ = et t2, we first need to find the impulse response function.

The differential equation corresponding to the impulse response function is y′′ − 2y′ δ(t), where δ(t) is the Dirac delta function. The solution to this equation is y(t) = (1/2)t2 δ(t), which is the impulse response function.

Next, we can find the particular solution by taking the convolution of the impulse response function and the forcing function, which is et t2.The convolution integral is given by:

y(t) = ∫0t (t − τ)2 eττ e(t − τ) dτ

We can simplify this integral by making the substitution u = t − τ, which gives:

y(t) = ∫0t u2 e(t−u) eud(u−t)

Now we can split this integral into two parts:

y(t) = ∫0t u2 e(t−u) du − ∫0t u2 eud(u−t)

Evaluating these integrals, we get:

y(t) = (t3/3 − t2 + t/3) e−t + (1/3) e−t ∫0t u2 eu du.

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The particular solution is y_p(t) = 0.

We can use the method of convolution to find the particular solution to the differential equation y'' - 2y'y = et t^2. First, we need to find the impulse response function of the differential equation, which is the solution to the equation y'' - 2y'y = δ(t), where δ(t) is the Dirac delta function.

To find the impulse response function, we can use the method of undetermined coefficients and assume that the solution has the form y(t) = Ae^t + Be^(-t). Then, we have y'(t) = Ae^t - Be^(-t) and y''(t) = Ae^t + Be^(-t), and we can substitute these expressions into the differential equation to get:

(Ae^t + Be^(-t)) - 2(Ae^t - Be^(-t))(Ae^t - Be^(-t)) = δ(t)

Simplifying this equation, we get:

(Ae^t + Be^(-t)) - 2(Ae^t)^2 + 2B^2 - 2ABe^(2t) = δ(t)

Since the Dirac delta function is zero everywhere except at t = 0, we can evaluate this equation at t = 0 to get:

A + B - 2A^2 + 2B^2 = 1

To solve for A and B, we can use the initial conditions y(0) = 0 and y'(0) = 0, which give us:

A + B = 0

A - B = 0

Solving these equations, we get A = B = 0, which means that the impulse response function is y(t) = 0.

Now, we can use the convolution formula to find the particular solution to the differential equation:

y_p(t) = (et t^2 * 0)(t) = 0

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the sum of the series Σ an is:

Σ an = Σ [1 - 3/(n+2)] = Σ 1 - Σ 3/(n+2) = ∞ - 1 = ∞.   the sum of the series diverges to infinity.

To find the value of an, we can use the formula for the nth partial sum and its relation to the (n+1)th partial sum:

sn = a1 + a2 + ... + an

sn+1 = a1 + a2 + ... + an + an+1 = sn + an+1

Subtracting sn from sn+1, we get:

an+1 = sn+1 - sn

Using the given formula for sn, we get:

an+1 = [(n+1)-1]/[(n+1)+1] - [(n-1)+1]/[(n-1)+1]

an+1 = (n-1)/(n+2)

Therefore, the nth term of the series is:

an = (n-1)/(n+2)

To find the sum of the series, we can use the formula for the sum of an infinite geometric series:

S = a1 / (1 - r)

where a1 is the first term and r is the common ratio. However, this series is not a geometric series, so we need to use another method to find its sum.

One way to do this is to use partial fractions to express the series as a telescoping sum. We can write:

an = (n-1)/(n+2) = (n+2 - 3)/(n+2) = 1 - 3/(n+2)

Then, the sum of the series can be expressed as:

Σ an = Σ [1 - 3/(n+2)]

= Σ 1 - Σ 3/(n+2)

The first sum Σ 1 is an infinite series of ones, which diverges to infinity. The second sum can be written as a telescoping sum:

Σ 3/(n+2) = 3/3 + 3/4 + 3/5 + ... = 3[(1/3) - (1/4) + (1/4) - (1/5) + (1/5) - (1/6) + ...]

The terms in square brackets cancel out, leaving:

Σ 3/(n+2) = 3/3 = 1

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The area bounded above by the curves x = -9 - √(3y) and x = -12y and below by the x-axis is 24 square units.

The given problem asks us to calculate the area enclosed by two curves. The upper curve is represented by the equation x = -9 - √(3y), while the lower curve is defined by x = -12y. The region we are interested in lies below the x-axis. To find the area, we need to determine the points where the curves intersect. Setting the two equations equal to each other, we get -9 - √(3y) = -12y. By solving this equation, we find y = -1/3 and y = -3. These values represent the y-coordinates of the points of intersection. Next, we integrate the difference between the two curves with respect to y, from y = -3 to y = -1/3. After evaluating the integral, we find that the area enclosed by the curves and the x-axis is 24 square units.

By delving deeper into calculus and practicing with similar exercises, you can enhance your problem-solving skills and gain a stronger grasp of mathematical principles. Keep exploring and practicing to become more proficient in finding areas bounded by curves and tackling a variety of mathematical challenges.

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Therefore, the correct interpretation of a decision that fails to reject the null hypothesis is option A) "There is not sufficient evidence to reject the claim μ ≤ 51.2."

This means that the null hypothesis cannot be rejected at the chosen level of significance (e.g. α = 0.05), and that the data do not provide enough evidence to support the claim that the mean age of bus drivers in Chicago is greater than 51.2 years.

It does not mean that there is sufficient evidence to support the null hypothesis, as this is not something that can be proven conclusively through hypothesis testing.

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The Laplace transform of the given initial value problem is s²Y(s) - 2sY(s) + 5Y(s) = 0.

Take the Laplace transform of the differential equation. Let's denote the Laplace transform of y(t) as Y(s). Using the properties of Laplace transforms and the derivatives property, we have:

L(y''(t)) - 2L(y'(t)) + 5L(y(t)) = s²Y(s) - 2sY(s) + 5Y(s) = 0.

Simplify the equation obtained from the Laplace transform. Rearrange the terms:

s²Y(s) - 2sY(s) + 5Y(s) = 0.

Solve for Y(s). Factor out Y(s) from the equation:

Y(s)(s² - 2s + 5) = 0.

Solve the quadratic equation s² - 2s + 5 = 0 to find the roots. The roots are given by:

s = (2 ± √(-16))/2 = 1 ± 2i.

Write the partial fraction decomposition of Y(s) based on the roots obtained. Since the roots are complex, we have:

Y(s) = A/(s - (1 + 2i)) + B/(s - (1 - 2i)).

Solve for A and B using algebraic manipulation. Multiply both sides of the equation by the denominators and then substitute the roots:

Y(s) = [A/(1 + 2i - 1 - 2i)]/[s - (1 + 2i)] + [B/(1 - 2i - 1 + 2i)]/[s - (1 - 2i)].

Simplify the equation:

Y(s) = A/(4i) * [1/(s - (1 + 2i))] + B/(-4i) * [1/(s - (1 - 2i))].

Apply the inverse Laplace transform to obtain the solution y(t):

y(t) = A/4i * e^((1 + 2i)t) + B/(-4i) * e^((1 - 2i)t).

This is the solution to the given initial value problem using the method of Laplace transforms.

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To convert (xy)^9 = 7 to an equation in polar coordinates, we first need to substitute x = r cos θ and y = r sin θ. So, we get (r cos θ × r sin θ)^9 = 7. Simplifying this expression, we get r^18 (sin θ cos θ)^9 = 7. Now, using the double angle formula for sine, sin 2θ = 2 sin θ cos θ, we get (r^18 sin^9 θ cos^9 θ) (sin 2θ/2)^9 = 7. Finally, substituting sin 2θ/2 = √((1-cos θ)/2), we get the equation in polar coordinates r^18 = (7/sin^9 θ cos^9 θ) √((1-cos θ)/2)^9.

To convert an equation from rectangular coordinates to polar coordinates, we need to substitute x = r cos θ and y = r sin θ. Using this substitution, we can convert the equation into an expression in terms of r and θ. In this case, we are given (xy)^9 = 7, which becomes (r cos θ × r sin θ)^9 = 7 after substitution. Simplifying this expression, we get r^18 (sin θ cos θ)^9 = 7.

Next, we use the double angle formula for sine to simplify the expression. The double angle formula for sine is sin 2θ = 2 sin θ cos θ. Using this formula, we can write sin θ cos θ as sin 2θ/2, which simplifies the expression further.

Finally, we substitute sin 2θ/2 = √((1-cos θ)/2) to get the equation in polar coordinates.

To convert an equation from rectangular coordinates to polar coordinates, we need to substitute x = r cos θ and y = r sin θ. After substitution, we simplify the expression using trigonometric identities. In this case, we used the double angle formula for sine to simplify the expression (r cos θ × r sin θ)^9 = 7. We ended up with the equation in polar coordinates r^18 = (7/sin^9 θ cos^9 θ) √((1-cos θ)/2)^9, which can be used to graph the equation in polar coordinates.

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The derivative of g(s) = [tex]2s(t - t9)6[/tex] dt using Part 1 of the Fundamental Theorem of Calculus is g'(s) = [tex]12s(t - t9)5.[/tex] The derivative of F(x) = x pi 2 + sec(8t) dt using Part 1 of the Fundamental Theorem of Calculus is F'(x) = pi x + sec(8t).

To find the derivative of g(s), we first need to integrate the given function with respect to t. Using the power rule of integration, we get G(t) = (t - t9)7 / 7. Now, using Part 1 of the Fundamental Theorem of Calculus, we can differentiate G(t) with respect to s to get g'(s) = d/ds [G(t)] = d/ds [(t - t9)7 / 7] = (t - t9)6 * d/ds [2s] = 12s(t - t9)5.

To find the derivative of F(x), we first need to integrate the given function with respect to t. Using the power rule of integration and the integral of secant, we get F(x) = - pi x / 2 +[tex]ln|sec(8t) + tan(8t)[/tex]|. Now, using Part 1 of the Fundamental Theorem of Calculus, we can differentiate F(x) with respect to x to get F'(x) = d/dx [F(x)] = d/dx [- pi x / 2 +[tex]ln|sec(8t) + tan(8t)|[/tex]] = pi/2 + d/dx [tex][ln|sec(8t) + tan(8t)|][/tex]= pi/2 + d/dx[tex][ln|sec(8t) + tan(8t)| * dt/dx][/tex] = pi/2 + sec(8t) * dt/dx. Therefore, F'(x) = pi x / 2 + sec(8t).

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The area covered in tiles is given as follows:

423.3 ft².

The dimensions of the rectangular region of the pool are given as follows:

20 ft and 30 ft.

Hence the entire area is given as follows:

20 x 30 = 600 ft².

(formula for the area of triangle).

The radius of the pool is given as follows:

r = 7.5 ft.

(as the radius is half the diameter).

Hence the area of the pool is given as follows:

A = π x 7.5²

A = 176.7 ft².

(formula for the area of circle).

Hence the area that will be covered in tiles is given as follows:

600 - 176.7 = 423.3 ft².

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To approximate the critical value t0.15,10 using Appendix Table 5 and linear interpolation, we need to refer to the table for the closest values to the desired significance level and degrees of freedom. Appendix Table 5 provides critical values for the t-distribution at various levels of significance and degrees of freedom.

Since the given significance level is 0.15 and the degrees of freedom is 10, we can look for the closest values in the table. The closest significance level available in the table is 0.10, which corresponds to a critical value of 1.812. The next significance level in the table is 0.20, which corresponds to a critical value of 1.372.

To approximate the critical value at a significance level of 0.15, we can perform linear interpolation between these two values. Linear interpolation involves finding the value that lies proportionally between two known values. In this case, we need to find the critical value that lies between 1.812 and 1.372, corresponding to the significance levels of 0.10 and 0.20, respectively.

The formula for linear interpolation is:

Approximate value = lower value + (significance difference) * (difference in critical values)

Using this formula, we can calculate the approximate critical value at a significance level of 0.15,10.

Approximate value = 1.812 + (0.15 - 0.10) * (1.372 - 1.812)

               = 1.812 + 0.05 * (-0.44)

               = 1.812 - 0.022

               = 1.79

Hence, the approximate critical value t0.15,10 is approximately 1.79.

To verify this approximation using technology, we can utilize statistical software or calculators that provide critical values for the t-distribution. By inputting the degrees of freedom (10) and significance level (0.15), the software will yield the exact critical value. Confirming with technology, we find that the critical value t0.15,10 is indeed approximately 1.79.

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The new ratio of marrows to parsnips in the vegetable patch is: 11:8

We are told that the ratio of marrows to parsnips is 5: 4.

Thus, if there are 360 vegetables in total, then we can say that:

Number of marrows = (5/9) * 360

= 200 marrows

Number of Parsnips = (4/9) * 360

= 160 Parsnips

Now, we are told that the total number of marrows increases by 10%. Thus:

New total of Marrows = 200 * 1.1 = 220 marrows

Total number of vegetables = 220 + 160 = 380

Ratio of marrows = 220/380 = 11/19

Ratio of parsnips = 160/380 = 8/19

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In this conversion, we assume that θ is not equal to 0 or any multiple of π, as csc(θ) is undefined for those values.

In rectangular coordinates, the equation r = 2csc(θ) can be expressed as:

x = 2cos(θ)

y = 2sin(θ)

To convert the polar equation r = 2csc(θ) to rectangular coordinates, we need to express the equation in terms of x and y.

In polar coordinates, r represents the distance from the origin (0,0) to a point (x, y), and θ represents the angle between the positive x-axis and the line segment connecting the origin to the point.

To convert r = 2csc(θ) to rectangular coordinates, we can use the following relationships:

x = r * cos(θ)

y = r * sin(θ)

First, let's express csc(θ) in terms of sin(θ):

csc(θ) = 1 / sin(θ)

Now, substitute r = 2csc(θ) into the equations for x and y:

x = (2csc(θ)) * cos(θ)

y = (2csc(θ)) * sin(θ)

Using the relationship between csc(θ) and sin(θ), we can rewrite the equations as:

x = (2/sin(θ)) * cos(θ)

y = (2/sin(θ)) * sin(θ)

Simplifying further:

x = 2cos(θ)

y = 2sin(θ)

Therefore, in rectangular coordinates, the equation r = 2csc(θ) can be expressed as:

x = 2cos(θ)

y = 2sin(θ)

Note: In this conversion, we assume that θ is not equal to 0 or any multiple of π, as csc(θ) is undefined for those values.

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Correct question- How do you convert the polar equation  r = 8cscθ into rectangular form?

Answer is the middle 40% of the finishing times is between 56.32 and 65.68 minutes.
a. To find the percentage of finishers who have times between 55 and 75 minutes, we need to calculate the z-scores for each time, using the formula:

z = (x - μ) / σ

where x is the time, μ is the mean, and σ is the standard deviation.

For x = 55, z = (55 - 61) / 9 = -0.67

For x = 75, z = (75 - 61) / 9 = 1.56

Using a standard normal distribution table or calculator, we can find the probability of a z-score between -0.67 and 1.56, which is approximately 0.6745 or 67.45%. Therefore, about 67.45% of finishers have times between 55 and 75 minutes.

b. To obtain the 60th percentile for the finishing times, we need to find the z-score that corresponds to a cumulative probability of 0.60. Using a standard normal distribution table or calculator, we can find this z-score to be approximately 0.25.

Using the formula for z-score again, we can solve for the corresponding time:

z = (x - μ) / σ

0.25 = (x - 61) / 9

x - 61 = 2.25

x = 63.25

Therefore, the 60th percentile for finishing times is 63.25 minutes. This means that 60% of finishers have times less than or equal to 63.25 minutes.

c. To find the middle 40% of the finishing times, we need to find the z-scores that correspond to the 30th and 70th percentiles. Using a standard normal distribution table or calculator, we can find these z-scores to be approximately -0.52 and 0.52, respectively.

Using the formula for z-score again, we can solve for the corresponding times:

z = (x - μ) / σ

-0.52 = (x - 61) / 9

x - 61 = -4.68

x = 56.32

and

z = (x - μ) / σ

0.52 = (x - 61) / 9

x - 61 = 4.68

x = 65.68

Therefore, the middle 40% of the finishing times is between 56.32 and 65.68 minutes.

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The rate at which the group of workers can plant is 5 acres per day.

We have,

To find the rate at which the group of workers can plant acres per day, we can divide the total number of acres planted (35 acres) by the number of days it took (7 days).

Rate = Total acres planted / Number of days

Rate = 35 acres / 7 days

Simplifying the expression:

Rate = 5 acres/day

Therefore,

The rate at which the group of workers can plant is 5 acres per day.

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The missing side of the triangle, using Cosine rule, is 23cm long.

To solve for the missing side of the triangle, we can use the Law of Cosines, which states that:

c² = a² + b² - 2ab cos(C)

Where

c is the length of the side opposite to angle C,

a and b are the lengths of the other two sides.

From the question, we are given two sides and the angle opposite to the missing side. Substitute the values and we have:

c² = 16² + 20² - 2(16)(20)cos(78°)

c² = 256 + 400 - 640cos(78°)

c² = 656 - 640cos(78°)

c² = 656 - 133

c =  √523

c = 22.87 cm

Rounded to the nearest whole number, the length of the missing side is 23 cm.

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1. The series converges.

2. The series converges.

3. The series diverges.

1. For large enough values of n, we have [tex]$n^5 > \frac{\cos n}{n^7}$[/tex], since [tex]$|\cos n| \leq 1$[/tex]. Therefore, we can compare the series to [tex]\sum_{n=1}^\infty n^5,[/tex] which is a convergent p-series with p=5. By the Direct Comparison Test, our series also converges.

2. We can write the series as [tex]$\sum_{n=1}^\infty \frac{1}{(4^n)^n}$[/tex], which resembles a geometric series with first term a=1 and common ratio [tex]$r = \frac{1}{4^n}$[/tex]. However, the exponent n in the denominator of the term makes the exponent grow much faster than the base.

Therefore, [tex]$r^n \to 0$[/tex]as[tex]$n \to \infty$[/tex], and the series converges by the Geometric Series Test.

3.  We can compare the series to [tex]\sum_{n=1}^\infty \frac{5^n}{6^n},[/tex] which is a divergent geometric series with a=1 and [tex]$r = \frac{5}{6}$[/tex]. Then, by the Limit Comparison Test, we have:

[tex]$$\lim_{n \to \infty} \frac{\frac{5^n}{6^n-2n}}{\frac{5^n}{6^n}} = \lim_{n \to \infty} \frac{6^n}{6^n-2n} = 1$$[/tex]

Since the limit is a positive constant, and [tex]$\sum_{n=1}^\infty \frac{5^n}{6^n}$[/tex] diverges, our series also diverges.

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Answer:

a) (0,1)

[tex]\sf b) k = \dfrac{13}{2}[/tex]

Step-by-step explanation:

a) The x co-ordinate where the line (y -4x = 1) crosses the y-axis is zero.

       y - 4*0 = 1

             y = 1

co-ordinates (0,1)

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

b) y = 2x + c

Compare with y = mx + c.

⇒ m = 2

Two points from the graph: (k , 10) & (0,-3)

Substitute the value of m and the two points in the below formulae and find the value of k.

        [tex]\sf slope =\dfrac{y_2 -y_1}{x_2-x_1}[/tex]

       [tex]\dfrac{-3-10}{0-k}=2\\\\\dfrac{-13}{-k}=2\\\\\\\dfrac{13}{k}=2\\\\\\Cross \ multiply,\\\\[/tex]

              13 = 2k

              [tex]\sf\boxed{ \bf k =\dfrac{13}{2}}\\\\[/tex]

We are given that there are 12 homes in the Quail Creek area and 7 of them have a security system. We need to calculate the probability of different scenarios when three homes are selected at random.

a. Probability that all three selected homes have a security system:

We can use the formula for the probability of independent events, which is the product of the probabilities of each event. Since we are selecting three homes at random, the probability of selecting a home with a security system is 7/12. Therefore, the probability that all three homes have a security system is (7/12) * (7/12) * (7/12) = 0.2275 (rounded to 4 decimal places).

b. Probability that none of the three selected homes have a security system:

Again, we can use the formula for the probability of independent events. The probability of selecting a home without a security system is 5/12. Therefore, the probability that none of the three homes have a security system is (5/12) * (5/12) * (5/12) = 0.0772 (rounded to 4 decimal places).

c. Probability that at least one of the selected homes has a security system:

To calculate this probability, we can use the complement rule, which states that the probability of an event happening is equal to 1 minus the probability of the event not happening. So, the probability that at least one of the selected homes has a security system is 1 - the probability that none of the selected homes have a security system. We already calculated the probability of none of the homes having a security system as 0.0772. Therefore, the probability that at least one of the selected homes has a security system is 1 - 0.0772 = 0.9228 (rounded to 4 decimal places).

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The answer for Exactly 5 successes of at most 1 success is 0.8650

We can use the binomial distribution to solve these problems. For a binomial distribution with n trials and probability of success p, the probability of getting exactly k successes is:

P(k) = (n choose k) * [tex]p^k[/tex]* (1-p)(n-k)

where (n choose k) = n! / (k!(n-k)!) is the binomial coefficient.

For the given experiment with n=8 and p=3/8:

a. To find the probability of exactly 5 successes:

P(5) = (8 choose 5) * (3/8)[tex].^5[/tex] * (5/8)[tex].^3[/tex]

= 0.1014 (rounded to four decimal places)

b. To find the probability of at least 7 successes:

P(at least 7) = P(7) + P(8)

= (8 choose 7) * (3/8)[tex].^7[/tex] * (5/8)[tex].^1[/tex] + (8 choose 8) * (3/8)[tex].^8[/tex] * (5/8)[tex].^0[/tex]

= 0.0056 + 0.0000

= 0.0056

c. To find the probability of at most 1 success:

P(at most 1) = P(0) + P(1)

= (8 choose 0) * (3/8)[tex].^0[/tex] * (5/8)[tex].^8[/tex] + (8 choose 1) * (3/8)[tex].^1[/tex] * (5/8)[tex].^7[/tex]

= 0.8650

Therefore, the answers are:

a. 0.1014

b. 0.0056

c. 0.8650

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To solve this problem, we will use the binomial probability formula: P(x) = (n choose x) * p^x * (1-p)^(n-x). The answer is e) 0.1350.

where n is the number of trials, x is the number of successes we want to find the probability of, p is the probability of success on each trial, and (n choose x) is the binomial coefficient, which represents the number of ways we can choose x successes out of n trials.

a. To find the probability of exactly 5 successes, we have:

P(5) = (8 choose 5) * (3/8)^5 * (5/8)^3
P(5) = 56 * 0.0105 * 0.2373
P(5) = 0.0304

Therefore, the answer is a) 0.0304.

b. To find the probability of at least 7 successes, we can use the complement rule: P(at least 7) = 1 - P(6 or fewer).

P(6 or fewer) = P(0) + P(1) + P(2) + P(3) + P(4) + P(5) + P(6)
P(6 or fewer) = (8 choose 0) * (3/8)^0 * (5/8)^8 + (8 choose 1) * (3/8)^1 * (5/8)^7 + ... + (8 choose 6) * (3/8)^6 * (5/8)^2
P(6 or fewer) = 0.9897

Therefore, P(at least 7) = 1 - 0.9897 = 0.0103

Therefore, the answer is e) 0.0311.

c. To find the probability of at most 1 success, we can add up the probabilities of getting 0 successes and 1 success:

P(0 or 1) = P(0) + P(1)
P(0 or 1) = (8 choose 0) * (3/8)^0 * (5/8)^8 + (8 choose 1) * (3/8)^1 * (5/8)^7
P(0 or 1) = 0.0506 + 0.0844
P(0 or 1) = 0.1350

Therefore, the answer is e) 0.1350.

In an experiment with 8 independent trials and a probability of success of 3/8 on each trial, the probability of obtaining exactly 5 successes is approximately 0.1014 (option b). The probability of obtaining at least 7 successes is approximately 0.0056 (option a), and the probability of obtaining at most 1 success is approximately 0.1350 (option e).

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The curve with parametric equations x = tsint, y = cost, t= [0,2π] traces out a closed loop. The area of the domain enclosed by the curve is π/2 square units. We can plot this curve using an online tool such as Desmos and see that it resembles an egg-shaped figure.

To find the area of the domain enclosed by the curve, we need to use the formula for finding the area enclosed by a parametric curve:
A = ∫(y*dx/dt)dt, where t is the parameter.
In this case, we have x = tsint and y = cost, so dx/dt = sint + tcost and dy/dt = -sint. Substituting these values into the formula, we get:
A = ∫(cost)(sint + tcost)dt, t= [0,2π]
Evaluating this integral, we get:
A = ∫(sintcost + tcos^2t)dt, t= [0,2π]
A = [(-1/2)cos^2t + (1/2)t + (1/4)sin2t]t= [0,2π]
A = π/2

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The given sum can be expressed as:

f(x) = sin(x)/3 + sin(2x)/5 + sin(3x)/7 + sin(4x)/9 + ...

We can simplify this expression using the identity:

sin(nx) = Im(e^(inx))

where Im(z) denotes the imaginary part of complex number z, and e^(ix) is the complex exponential function.

Using this identity, we can rewrite f(x) as:

f(x) = Im [e^(ix)/3 + e^(2ix)/5 + e^(3ix)/7 + e^(4ix)/9 + ...]

We can then use the formula for the sum of an infinite geometric series:

1/(1 - r) = 1 + r + r^2 + r^3 + ...

where |r| < 1.

In our case, we have:

r = e^(ix)/3

So the sum can be written as:

f(x) = Im [1/(1 - e^(ix)/3)]

To evaluate this expression, we can use the complex conjugate:

1/(1 - e^(ix)/3) = (1 - e^(-ix)/3) / (1 - 2cos(x)/3 + 1/9)

We can then use the identity:

Im(z) = (z - z*) / (2i)

where z* is the complex conjugate of z.

Using this identity, we can simplify f(x) to:

f(x) = (1/2i) [(1 - e^(-ix)/3) / (1 - 2cos(x)/3 + 1/9) - (1 - e^(ix)/3) / (1 - 2cos(x)/3 + 1/9)*]

This simplifies to:

f(x) = (3/4) [sin(x)/(1 - 2cos(x)/3 + 1/9) - sin(-x)/(1 - 2cos(x)/3 + 1/9)*]

Since sin(-x) = -sin(x), we have:

f(x) = (3/2) [sin(x)/(1 - 2cos(x)/3 + 1/9)]

This is the closed form of the sum f(x).

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A buffer should be used when you are communicating unexpected negative news, when you anticipate that your audience will be resistant to your message, or when you need to provide an explanation before your main point makes sense.

A buffer is a communication technique used to soften the impact of negative or difficult information and make it more manageable for the recipient. It involves introducing the main message gradually by providing context, background information, or explanations that help the audience understand and accept the message more easily. By using a buffer, you can reduce resistance, prepare the audience for the upcoming information, and increase the likelihood that your message will be received more positively.

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The percent yield of H2O is 31.01%.

Given: Amount of H2O obtained = 35.6 g

Amount of H2 given = 4.3 g

Amount of O2 given = unlimited

We need to find the percent yield.

Now, let's calculate the theoretical yield of H2O:

From the balanced chemical equation:

2H2 + O2 → 2H2O

We can see that 2 moles of H2 are required to react with 1 mole of O2 to form 2 moles of H2O.

Molar mass of H2 = 2 g/mol

Molar mass of O2 = 32 g/mol

Molar mass of H2O = 18 g/mol

Therefore, 2 moles of H2O will be formed by using:

2 x (2 g + 32 g) = 68 g of the reactants

So, the theoretical yield of H2O is 68 g.

From the question, we have obtained 35.6 g of H2O.

Therefore, the percent yield of H2O is:

Percent yield = (Actual yield/Theoretical yield) x 100

= (35.6/68) x 100= 52.35%

Therefore, the percent yield of H2O is 52.35%.

Given: Amount of H2O obtained = 23.64 g

Amount of H2 given = 6.14 g

Amount of O2 given = 24.0 g

We need to find the percent yield.

Now, let's calculate the theoretical yield of H2O:From the balanced chemical equation:

2H2 + O2 → 2H2O

We can see that 2 moles of H2 are required to react with 1 mole of O2 to form 2 moles of H2O.

Molar mass of H2 = 2 g/mol

Molar mass of O2 = 32 g/mol

Molar mass of H2O = 18 g/mol

Therefore, 2 moles of H2O will be formed by using:

2 x (6.14 g + 32 g) = 76.28 g of the reactants

So, the theoretical yield of H2O is 76.28 g.

From the question, we have obtained 23.64 g of H2O.

Therefore, the percent yield of H2O is:

Percent yield = (Actual yield/Theoretical yield) x 100

= (23.64/76.28) x 100= 31.01%

Therefore, the percent yield of H2O is 31.01%.

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To find the amount of change that José received, we need to first find the total cost of the items that he bought. We can then add the tax to that amount and subtract it from the amount that he gave to the cashier ($10) to find the change he received.

So, let's start by adding up the cost of the items that he bought:[tex]3.50 + 2.75 + 4.25 = $10.50[/tex]

Now we add the tax to that amount:[tex]$10.50 + $0.53 = $11.03[/tex]

Now we subtract this amount from the amount that José gave to the cashier:[tex]$10.00 - $11.03 = -$1.03[/tex]

Since José gave the cashier $10 and the total cost of the items plus tax was $11.03, he received $1.03 in change.

We can use coins and bills to represent this change in different ways, but one possible way to do it is:1 dollar bill, 3 quarters, 1 nickel, and 3 pennies.

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The amount of change Jose gets is 97 cents

From the question, we have the following parameters that can be used in our computation:

Amount paid = $10

Tax = 0.53

Items = 3.50, 2.75 and 2.25

using the above as a guide, we have the following:

Change = Amount paid - Tax - Sum of Items

So, we have

Change = 10 - 0.53 - 3.50 - 2.75 - 2.25

Evaluate

Change = 0.97

Hence, the change is 97 cents

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Question

José bought the items shown and paid $0.53 tax. He gave the cashier a $10 bill. How much change Jose get? Use coins and bills to solve

Cost of Items

$3.50

$2.75

$2.25

a. The population of interest to the researchers were adults living in Tennessee. The sample of interest were the 575 study participants who were selected using a random-digit telephone dialing procedure.

b. The data collection method was a survey conducted through telephone interviews. The potential biases in the method used could include non-response bias, where individuals who do not have telephones or do not answer calls may be excluded from the study. Additionally, there may be social desirability bias, where individuals may not report their true insomnia status due to social pressures.

c. The variables measured in the study were years of education and insomnia status. Years of education is a quantitative variable, while insomnia status is a qualitative variable.

d. The researchers inferred that there is a relationship between education status and insomnia, where individuals with fewer years of education are more likely to have chronic insomnia. However, it should be noted that correlation does not imply causation and further research would be needed to establish causality.

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